Decision analytics may appear to some as the light at the end of the tunnel, but most will experience it as the oncoming train that is hard to dodge. Decision analytics is the process of rendering decisions supported by analytic capabilities that improve the decision-making process and reduce decision time, complexity, and uncertainty. Decision analytics will have a transformative impact on the IT market. This union of decisioning tools and advanced analytics enables enterprises to become more precise and confident in making complex forward-looking decisions. To date, IT and BI have been all about understanding the past and present. A comprehensive understanding of the past and present is invaluable and is a critical prerequisite for making forward-looking decisions. However, in order to effectively make informed forward-looking decisions that will have lasting utility, reliance on predictive analytic techniques is paramount. Enterprises should understand the potential value that can be delivered through predictive intelligence and carefully consider creating a decision analytics programs office led by a chief data officer.

The remainder of this document focuses on the architectural model needed to support decision analytics, the categories of analytics that are leveraged in decision analytics, the subset of decision analytics that supports predictive intelligence, and some of the more common use cases for decision analytics.

The decision analytics journey will be challenging, but can be greatly simplified based on:

The commitment of the enterprise to utilize decision analytics.

The identification of decision analytics objectives.

Astute choices made regarding a decision analytics architecture.

The careful selection of your decision analytics product and service technology partners.